This invention relates to the field of digital signal processing employing frequency subband processing methods.
Frequency subband processing schemes are used in various practical applications in the communications field. They include but are not limited to acoustic echo cancellation, noise suppression, multiband dynamic range compression and microphone arrays. In many cases, subband technologies possess multiple advantages compared to their full band counterparts. For example, by using subband adaptive filtering processing algorithms, the significant reduction in computational complexity of adaptive filters can be achieved with the simultaneous improvement of both convergence and robustness. Dividing (splitting) original noisy signals into frequency subbands and adjusting each subband's gain opens a way to the efficient suppression of stationary noises without the so called “noise modulation” effect typical for the full band “noise gaiting” approach. Subband dynamic range compression leads to improvements in speech ineligibility in noisy environments by selectively and dynamically amplifying spectral regions where information is masked by ambient noise.
Subband decomposition schemes differ in:                a computational scheme;        a number of frequency subbands;        a frequency overlap between adjacent subbands;        a downsampling factor for the subband signals.        
In regards to downsampling, subband decomposition schemes can be divided into two main classes:                schemes employing downsampling, that is producing output subband signals with reduced sampling rate; and        schemes without downsampling, in which schemes the output subband signals have an original sampling rate with only a part of an available full band spectrum used by subband signals.        
FIG. 1 illustrates principles of subband decomposition and processing with downsampling. An input full band signal is first processed by an Analysis block where it is divided into N frequency subband signals (1, 2, . . . N). Each subband signal is then processed independently by its own Processing block. Processed subband signals are then recombined in a Synthesis block.
The Analysis block can be conceptually represented as comprising N Frequency Shifting (FS) subblocks, with each FS subblock followed by a Low Pass Filter (LPF) subblock and a downsampling subblock M for downsampling a filtered subband signal by a factor M. Each Frequency Shifting subblock shifts the input signal down in frequency so that the corresponding subband frequency region is located in the low frequencies. The following low pass filtering ensures that no spectral aliasing occurs after the downsampling stage, where each M-th sample is taken for forming the output subband signal.
The Synthesis block may be conceptually represented as comprising N upsampling subblocks for upsampling N processed subband signals by factor M and N LPF subblocks followed by N Inverse Frequency Shifting (IFS) subblocks. Upsampling by factor M can be performed by inserting M−1 zeros between processed subband samples. Corresponding replicas of the original subband spectrum are filtered out by the LPF subblocks. Finally, the IFS subblocks shift the filtered subband signals back in frequency into the corresponding frequency regions. Output subband signals are then summed up to produce a full band output signal.
The structure of the Analysis and Synthesis blocks described above was presented for illustration purposes only. Real devices can implement different sequences of operations for both analysis and synthesis as well as different computation schemes. Reference may be made here to R. E. Crochiere, L. R. Rabiner. “Multirate Digital Signal Processing”, Prentice Hall, 1983, and P. P. Vaidyanathan. “Multirate Devices and Filter Banks”, Prentice Hall, 1993. Subband processing with downsampling is further described in a number of patent publications, including, among many others, U.S. Pat. Nos. 7,003,101 (disclosing a method of controlling an echo canceller in a communications channel) and 7,010,119 (disclosing an echo canceller for an audio communication device).
Imperfect low-pass filtering before downsampling in the analysis stage and after upsampling in the synthesis stage results in frequency aliasing and corresponding distortions in the output full band signal. Subband decomposition with downsampling without aliasing requires a perfect frequency separation between bands, which is impossible to attain with real, finite length or finite order filters. Therefore, in practice some aliasing is always present with its maximal allowed level depending on a specific application. For real frequency subbands (subband samples are real numbers), the theoretical limit of downsampling factor without aliasing is equal to a number of subbands (M=N). Perfect frequency separation between subbands requires infinite order filters and for that reason cannot be implemented in practice. With a chosen low-pass filter order and a specified number N of frequency subbands, the level of aliasing can be reduced by using a lower downsampling factor M. However, such approach also reduces computational advantages of using subband processing schemes in certain types of applications (i.e such as adaptive filtering).
The length of the low-pas filters is generally chosen to provide an acceptable tradeoff between:                maximizing the number N of frequency subbands to attain a maximal frequency resolution; —maximizing the downsampling ratio M/N to attain the maximal reduction of computational complexity; —minimizing the level of frequency aliasing to reduce output signal distortions; and—minimizing the order of the low-pass filter to reduce a filter group delay.        
FIG. 2 illustrates a much simpler concept of subband decomposition and processing without downsampling. The input full band signal is divided into N frequency subband signals with a set of Band Pass Filter (BPF) subblocks. Since no downsampling is performed, the frequency subband signals can have a significant overlap, so that simple, relatively low group delay filters can be used. However, the computational advantages of the downsampling scheme of FIG. 1 are not available. Subband processing without downsampling is also described in a number of patent publications, such as U.S. Pat. Nos. 5,242,695 and 6,266,760 (both disclosing a subband echo canceller for audio applications); and U.S. Pat. No. 6,970,558 (disclosing an application of subband processing for suppressing noise in telephone devices).
In a typical communication device some digital signal processing tasks require high frequency resolution while others can perform well with only a moderate resolution. To give an example, when using the standard communication sampling rate of 8 kHz, a subband acoustic echo canceller and residual echo suppressor can perform well with the number of subbands as low as 4. In many applications, the computation scheme with downsampling is generally preferable due to computational advantages it provides. However, when a high frequency resolution is required, the downsampling/upsampling operations can introduce a substantial delay into signal processing. For example, good quality noise suppression requires a frequency resolution better than 50 Hz. For the sampling frequencies of 8 kHz and 32 kHz, it means a necessity of having respectively at least 80 subbands and at least 320 subbands. If such narrow subbands are used with substantial downsampling, the downsampling scheme (such as shown in FIG. 1) will introduce about 100 ms delay into the computational process. Such large delay is unacceptable for a majority of voice communication devices, in which devices subband processing in real time is generally required.
For the above reasons, there exists a long-felt need in effective means for subband processing of various input signals with providing the computational gains characteristic for the downsampling schemes, while at the same time substantially reducing disadvantages of such schemes when using a high frequency resolution.